Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

Thomas Kemper; Lionel Gueguen; Pierre Soille

doi:10.1117/12.919841

14 May 2012 Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite

Thomas Kemper, Lionel Gueguen, Pierre Soille

Author Affiliations +

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 83900M (2012) https://doi.org/10.1117/12.919841
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

The enumeration of the population remains a critical task in the management of refugee/IDP camps. Analysis of very high spatial resolution satellite data proofed to be an efficient and secure approach for the estimation of dwellings and the monitoring of the camp over time. In this paper we propose a new methodology for the automated extraction of features based on differential morphological decomposition segmentation for feature extraction and interactive training sample selection from the max-tree and min-tree structures. This feature extraction methodology is tested on a WorldView-2 scene of an IDP camp in Darfur Sudan. Special emphasis is given to the additional available bands of the WorldView-2 sensor. The results obtained show that the interactive image information tool is performing very well by tuning the feature extraction to the local conditions. The analysis of different spectral subsets shows that it is possible to obtain good results already with an RGB combination, but by increasing the number of spectral bands the detection of dwellings becomes more accurate. Best results were obtained using all eight bands of WorldView-2 satellite.

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Thomas Kemper, Lionel Gueguen, and Pierre Soille "Improving the automated detection of refugee/IDP dwellings using the multispectral bands of the WorldView-2 satellite", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83900M (14 May 2012); https://doi.org/10.1117/12.919841

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KEYWORDS

Visualization

RGB color model

Satellites

Feature extraction

Mining

Spatial resolution

Sensors

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